Modern organizations increasingly rely on real-time decision-making, often driven by high-performance, highly accurate AI models. To ensure these models reflect the most current operational data, it's essential to equip application infrastructures with robust change data capture (CDC) capabilities. Meanwhile, data and analytics professionals are turning to advanced techniques like retrieval-augmented generation (RAG) to ground AI models in trusted knowledge sources.
When CDC and RAG are deployed together within enterprise IT infrastructures, they guarantee that the latest data updates are instantly fed into downstream applications. This ensures AI outputs remain accurate and relevant, even during disruptions, and enhances system resilience by reducing downtime, data loss, and recovery time.
In this webinar, TDWI senior research director James Kobielus will discuss how CDC and RAG can become pivotal infrastructure for enterprise AI-driven decisioning and IT system resilience strategies. He will be joined by Spencer Cook, senior solutions architect from Databricks, and John Kutay, director of product and engineering from Striim, for a deep dive of the necessary practices, platforms, and other investments that organizations must make to realize these mission-critical outcomes. They will cover:
- How AI-driven real-time decisioning systems can contribute to business success
- The critical role of CDC in building high-performance AI-driven decision-making applications
- How CDC enhances the performance of RAG models, bolstering the trustworthiness and resilience of AI deployments
- CDC’s role in real-time observability of database changes that impact AI and other mission-critical applications
- How CDC boosts IT resilience, ensures proactive anomaly detection and adaptive response, and accelerates AI system recovery from disruptions
